{"id":"W1562188241","doi":"10.1002/asjc.1151","title":"State Estimation of Stochastic Impulsive System Via Stochastic Adaptive Impulsive Observer","year":2015,"lang":"en","type":"article","venue":"Asian Journal of Control","topic":"Adaptive Control of Nonlinear Systems","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Observer (physics); Control theory (sociology); Nonlinear system; Parametric statistics; State (computer science); State observer; Mathematics; Stochastic process; Estimation; Computer science; Engineering; Control (management); Algorithm; Statistics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007024808,0.0003457241,0.001040264,0.0003142495,0.00003531221,0.00003364586,0.0003443209,0.0001128934,0.00000627814],"category_scores_gemma":[0.0003142299,0.0003072367,0.0002688021,0.0002138491,0.0000816178,0.0004992046,0.00002136455,0.0003842227,0.00004201446],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004598809,"about_ca_system_score_gemma":0.0002285133,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001359996,"about_ca_topic_score_gemma":0.000008319636,"domain_scores_codex":[0.9973027,0.0001970453,0.001280252,0.0001614839,0.0006651434,0.0003934398],"domain_scores_gemma":[0.9968086,0.0002359646,0.001007459,0.0002600256,0.001272929,0.0004150159],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005967151,0.00003247581,0.00002800699,0.00007142484,0.00072456,0.0001038337,0.001324828,0.9897943,0.0007688183,0.0001830041,0.0001734442,0.00619861],"study_design_scores_gemma":[0.006884569,0.001131216,0.001011017,0.000577189,0.0003416295,0.0005068205,0.002255543,0.9864603,0.00008419458,0.0004153899,0.00001230706,0.0003198841],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02353185,0.001205861,0.9730879,0.0000828421,0.001137901,0.0005696556,0.00007281462,0.00006391671,0.0002472257],"genre_scores_gemma":[0.9975032,6.30707e-7,0.002009734,0.00001407053,0.000360431,0.00001283484,0.000002939882,0.00007238071,0.0000237528],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9739714,"threshold_uncertainty_score":0.999938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01155270782899733,"score_gpt":0.2167435261005566,"score_spread":0.2051908182715593,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}